Bioindication and modelling of atmospheric deposition in forests enable exposure and effect monitoring at high spatial density across scales

Schröder, Winfried; Nickel, Stefan; Schönrock, Simon; Schmalfuß, Roman; Wosniok, Werner; Meyer, Michaela; Harmens, Harry; Frontasyeva, Marina V.; Alber, Renate; Aleksiayenak, Julia; Barandovski, Lambe; Blum, Oleg; Carballeira, Alejo; Dam, Maria; Danielsson, Helena; De Temmerman, Ludwig; Dunaev, Anatoly M.; Godzik, Barbara; Hoydal, Katrin; Jeran, Zvonka; Karlsson, Gunilla Pihl; Lazo, Pranvera; Leblond, Sebastien; Lindroos, Jussi; Liiv, Siiri; Magnússon, Sigurður H.; Mankovska, Blanka; Núñez-Olivera, Encarnación; Piispanen, Juha; Poikolainen, Jarmo; Popescu, Ion V.; Qarri, Flora; Santamaria, Jesus Miguel; Skudnik, Mitja; Špirić, Zdravko; Stafilov, Trajce; Steinnes, Eiliv; Stihi, Claudia; Suchara, Ivan; Thöni, Lotti; Uggerud, Hilde Thelle; Zechmeister, Harald G.. 2017 Bioindication and modelling of atmospheric deposition in forests enable exposure and effect monitoring at high spatial density across scales. Annals of Forest Science, 74 (2), 31. 23, pp. https://doi.org/10.1007/s13595-017-0621-6

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Official URL: http://dx.doi.org/10.1007/s13595-017-0621-6

Abstract/Summary

Context: For enhancing the spatial resolution of measuring and mapping atmospheric deposition by technical devices and by modelling, moss is used complementarily as bio-monitor. Aims: This paper investigated whether nitrogen and heavy metal concentrations derived by biomonitoring of atmospheric deposition are statistically meaningful in terms of compliance with minimum sample size across several spatial levels (objective 1), whether this is also true in terms of geostatistical criteria such as spatial auto-correlation and, by this, estimated values for unsampled locations (objective 2) and whether moss indicates atmospheric deposition in a similar way as modelled deposition, tree foliage and natural surface soil at the European and country level, and whether they indicate site-specific variance due to canopy drip (objective 3). Methods: Data from modelling and biomonitoring atmospheric deposition were statistically analysed by means of minimum sample size calculation, by geostatistics as well as by bivariate correlation analyses and by multivariate correlation analyses using the Classification and Regression Tree approach and the Random Forests method. Results: It was found that the compliance of measurements with the minimum sample size varies by spatial scale and element measured. For unsampled locations, estimation could be derived. Statistically significant correlations between concentrations of heavy metals and nitrogen in moss and modelled atmospheric deposition, and concentrations in leaves, needles and soil were found. Significant influence of canopy drip on nitrogen concentration in moss was proven. Conclusion: Moss surveys should complement modelled atmospheric deposition data as well as other biomonitoring approaches and offer a great potential for various terrestrial monitoring programmes dealing with exposure and effects.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1007/s13595-017-0621-6
UKCEH and CEH Sections/Science Areas:	Emmett
ISSN:	1286-4560
Additional Keywords:	bioaccumulation, biomonitoring, EMEP, environmental specimen bank, ICP Forests Level II, LOTOS-EUROS
NORA Subject Terms:	Ecology and Environment Atmospheric Sciences Botany
Related URLs:	Project Website
Date made live:	09 May 2017 14:51 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/516853

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1007/s13595-017-0621-6

UKCEH and CEH Sections/Science Areas:

Emmett

ISSN:

1286-4560

Additional Keywords:

bioaccumulation, biomonitoring, EMEP, environmental specimen bank, ICP Forests Level II, LOTOS-EUROS

NORA Subject Terms:

Ecology and Environment
Atmospheric Sciences
Botany